Figueroa Caroline A, Torkamaan Helma, Bhattacharjee Ananya, Hauptmann Hanna, Guan Kathleen W, Sedrakyan Gayane
Faculty of Technology, Policy and Management, Delft University of Technology, Delft, Netherlands.
School of Social Welfare, University of California, Berkeley, Berkeley, CA, United States.
J Med Internet Res. 2025 Jan 30;27:e60138. doi: 10.2196/60138.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities. We use the socioecological model, which provides representations of how multiple, nested levels of influence (eg, community, institutional, and policy factors) interact to shape individual health. This perspective helps illustrate how HRS could address not just individual health factors but also the structural barriers-such as access to health care, social support, and access to healthy food-that shape health outcomes at various levels. Based on this analysis, we then discuss the challenges and future research priorities. We find that despite the potential for targeting more complex systemic challenges to obtaining good health, current HRS are still focused on individual health behaviors, often do not integrate the lived experiences of users in the design, and have had limited reach and effectiveness for individuals from low socioeconomic status and racial or ethnic minoritized backgrounds. In this viewpoint, we argue that a new design paradigm is necessary in which HRS focus on incorporating structural barriers to good health in addition to user preferences. HRS should be designed with an emphasis on health systems, which also includes incorporating decolonial perspectives of well-being that challenge prevailing medical models. Furthermore, potential lies in evaluating the health equity effects of HRS and leveraging collected data to influence policy. With changes in practices and with an intentional equity focus, HRS could play a crucial role in health promotion and decreasing health inequities.
健康推荐系统(HRS)有能力通过个性化内容,如健康干预措施或健康信息,来改善以人为主的护理和预防工作。HRS是一个新兴且不断发展的领域,在数字健康领域可发挥独特作用,因为它们不仅能根据用户自身的偏好和可能接受的内容提供相关推荐,还能利用有关对人类行为有更广泛影响范围的数据,包括同龄人、家庭、社区和社会。我们识别并讨论了HRS如何在减少健康不平等方面发挥独特作用。我们使用社会生态模型,该模型呈现了多个嵌套影响层面(如社区、机构和政策因素)如何相互作用以塑造个体健康。这种视角有助于说明HRS不仅可以解决个体健康因素,还能解决在各个层面塑造健康结果的结构性障碍,如获得医疗保健、社会支持以及获取健康食品的机会。基于此分析,我们接着讨论了挑战和未来的研究重点。我们发现,尽管HRS有潜力针对获得良好健康的更复杂系统性挑战,但目前它们仍专注于个体健康行为,在设计中往往没有整合用户的实际生活经历,对社会经济地位低以及少数族裔背景的个人而言,其覆盖范围和效果有限。在本文观点中,我们认为需要一种新的设计范式,即HRS除了关注用户偏好外,还应注重纳入影响良好健康的结构性障碍。HRS的设计应强调健康系统,这还包括纳入挑战主流医学模式的非殖民化幸福观。此外,评估HRS对健康公平的影响并利用收集到的数据来影响政策具有潜力。随着实践的改变以及有意关注公平性,HRS在健康促进和减少健康不平等方面可发挥关键作用。